Dataset Information

In vitro, long-range sequence information for de novo genome assembly via transposase contiguity.

ABSTRACT: We describe a method that exploits contiguity preserving transposase sequencing (CPT-seq) to facilitate the scaffolding of de novo genome assemblies. CPT-seq is an entirely in vitro means of generating libraries comprised of 9216 indexed pools, each of which contains thousands of sparsely sequenced long fragments ranging from 5 kilobases to > 1 megabase. These pools are "subhaploid," in that the lengths of fragments contained in each pool sums to ?5% to 10% of the full genome. The scaffolding approach described here, termed fragScaff, leverages coincidences between the content of different pools as a source of contiguity information. Specifically, CPT-seq data is mapped to a de novo genome assembly, followed by the identification of pairs of contigs or scaffolds whose ends disproportionately co-occur in the same indexed pools, consistent with true adjacency in the genome. Such candidate "joins" are used to construct a graph, which is then resolved by a minimum spanning tree. As a proof-of-concept, we apply CPT-seq and fragScaff to substantially boost the contiguity of de novo assemblies of the human, mouse, and fly genomes, increasing the scaffold N50 of de novo assemblies by eight- to 57-fold with high accuracy. We also demonstrate that fragScaff is complementary to Hi-C-based contact probability maps, providing midrange contiguity to support robust, accurate chromosome-scale de novo genome assemblies without the need for laborious in vivo cloning steps. Finally, we demonstrate CPT-seq as a means of anchoring unplaced novel human contigs to the reference genome as well as for detecting misassembled sequences.

SUBMITTER: Adey A

PROVIDER: S-EPMC4248320 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

In vitro, long-range sequence information for de novo genome assembly via transposase contiguity.

Adey Andrew A Kitzman Jacob O JO Burton Joshua N JN Daza Riza R Kumar Akash A Christiansen Lena L Ronaghi Mostafa M Amini Sasan S Gunderson Kevin L KL Steemers Frank J FJ Shendure Jay J

Genome research 20141019 12

We describe a method that exploits contiguity preserving transposase sequencing (CPT-seq) to facilitate the scaffolding of de novo genome assemblies. CPT-seq is an entirely in vitro means of generating libraries comprised of 9216 indexed pools, each of which contains thousands of sparsely sequenced long fragments ranging from 5 kilobases to > 1 megabase. These pools are "subhaploid," in that the lengths of fragments contained in each pool sums to ∼5% to 10% of the full genome. The scaffolding ap ...[more]

PMID: 25327137

Similar Datasets

Project description:BackgroundThe ability to generate recombinant drug target proteins is important for drug discovery research as it facilitates the investigation of drug-target-interactions in vitro. To accomplish this, the target's exact protein sequence is required. Public databases, such as Ensembl, UniProt and RefSeq, are extensive protein and nucleotide sequence repositories. However, many sequences for non-human organisms are predicted by computational pipelines and may thus be incomplete or incorrect. This could lead to misinterpreted experimental outcomes due to gaps or errors in orthologous drug target sequences. Transcriptome analysis by RNA-Seq has been established as a standard method for gene expression analysis. Apart from this common application, paired-end RNA-Seq data can also be used to obtain full coverage cDNA sequences via de novo transcriptome assembly.MethodsTo assess whether de novo transcriptome assemblies can be used to determine a protein's sequence by searching the assembly for a known orthologous sequence, we generated 3 × 6 = 18 tissue specific assemblies (three organs: brain, kidney and liver; six species: human, mouse, rat, dog, pig and cynomolgus monkey). These assemblies and the manually curated human protein sequences from UniProtKB/Swiss-Prot were used in a reciprocal BLAST search to identify best matching hits. We automated and generalised our approach and present the a&o-tool, a workflow which exploits de novo assemblies of paired-end RNA-Seq data and orthology information for target sequence validation and refinement across related species. Furthermore, the a&o-tool extracts best hits' sequences from a reciprocal BLAST search, translates them into protein sequences, computes a multiple sequence alignment and quantifies the refinement.ResultsFor the three human assemblies we observed a hit rate greater than 60% with 100% sequence coverage and identity. For assemblies from the other species we observed similar hit rates and coverage with highest identities for cynomolgus monkey.ConclusionsIn summary, we show how to refine protein sequences using RNA-Seq data and sequence information from closely related species. With the a&o-tool we provide a fully automated pipeline to perform refinement including cDNA translation and multiple sequence alignment for visual inspection. The major prerequisite for applying the a&o-tool is high quality sequencing data.

Project description:The whole-genome sequence assembly (WGSA) problem is among one of the most studied problems in computational biology. Despite the availability of a plethora of tools (i.e., assemblers), all claiming to have solved the WGSA problem, little has been done to systematically compare their accuracy and power. Traditional methods rely on standard metrics and read simulation: while on the one hand, metrics like N50 and number of contigs focus only on size without proportionately emphasizing the information about the correctness of the assembly, comparisons performed on simulated dataset, on the other hand, can be highly biased by the non-realistic assumptions in the underlying read generator. Recently the Feature Response Curve (FRC) method was proposed to assess the overall assembly quality and correctness: FRC transparently captures the trade-offs between contigs' quality against their sizes. Nevertheless, the relationship among the different features and their relative importance remains unknown. In particular, FRC cannot account for the correlation among the different features. We analyzed the correlation among different features in order to better describe their relationships and their importance in gauging assembly quality and correctness. In particular, using multivariate techniques like principal and independent component analysis we were able to estimate the "excess-dimensionality" of the feature space. Moreover, principal component analysis allowed us to show how poorly the acclaimed N50 metric describes the assembly quality. Applying independent component analysis we identified a subset of features that better describe the assemblers performances. We demonstrated that by focusing on a reduced set of highly informative features we can use the FRC curve to better describe and compare the performances of different assemblers. Moreover, as a by-product of our analysis, we discovered how often evaluation based on simulated data, obtained with state of the art simulators, lead to not-so-realistic results.

Dataset Information

In vitro, long-range sequence information for de novo genome assembly via transposase contiguity.

Publications

In vitro, long-range sequence information for de novo genome assembly via transposase contiguity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets